High-pressure melting and elastic behavior of vanadium and niobium based on ab initio and machine learning molecular dynamics
Hao Wang, Dan Wang, Long Hao, Jun Li, Hua Y. Geng

TL;DR
This study combines ab initio and machine learning molecular dynamics to explore high-pressure melting and elastic behaviors of vanadium and niobium, revealing phase stability, melting lines, and temperature-dependent elastic anomalies.
Contribution
It introduces a combined AIMD and MLMD approach to accurately model melting and elastic behaviors of V and Nb under high pressure, including phase stability and anomalous properties.
Findings
Nb's high-temperature Pnma phase is mechanically unstable and reverts to BCC.
The melting temperature of Nb is higher than previous estimates.
Atomic thermal displacements influence elastic properties more than electron temperature.
Abstract
Under high pressure, the group-VB transition metals vanadium (V) and niobium (Nb) exhibit simple crystal structures but complex physical behaviors, such as anomalous compression-induced softening and heating-induced hardening (CISHIH). Meanwhile, the impact of lattice thermal expansion-induced softening at elevated temperatures on HIH is yet to be investigated. Therefore, this study utilized ab initio (AIMD) and machine learning molecular dynamics (MLMD) to investigate the melting and abnormal mechanical softening-hardening behaviors of V and Nb under high pressure. Simulations reveal that the high-temperature Pnma phase of Nb reported in previous experimental studies is highly susceptible to mechanical instability and reverts to the body-centered cubic (BCC) phase. This discovery prompted a revised determination of the high-pressure melting line of Nb. The melting temperature of Nb…
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Taxonomy
TopicsHigh-pressure geophysics and materials · Boron and Carbon Nanomaterials Research · Machine Learning in Materials Science
